朴素
发表于 2025-3-25 06:50:34
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蹒跚
发表于 2025-3-25 11:18:37
Some Results Independent of Specific Distributions,We could start out and derive some of the standard probability distributions. However, some very important and deep results are independent of individual distributions. It is very easy to think that many results are true for normal distributions only when in fact they are generally true.
reperfusion
发表于 2025-3-25 12:31:10
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魅力
发表于 2025-3-25 17:46:17
Inverse Probability; Confidence Limits,Suppose we have a set of a great many systems of . mutually exclusive kinds, i.e., systems of kinds .., .., ..., ... Suppose further that we randomly pick a system and perform an experiment on it getting the result .. What is the probability that we have a system of kind .?
吃掉
发表于 2025-3-25 22:04:27
Fitting Data with Correlations and Constraints,Until now, we have usually taken individual measurements as independent. This is often not the case. Furthermore, there may be constraints on the values. We will examine here a general formalism for dealing with these complications if the problem can be approximately linearized and if the errors on each point are approximately normal.
军火
发表于 2025-3-26 02:28:56
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Anguish
发表于 2025-3-26 07:36:43
Discrete Distributions and Combinatorials,pplications and that we further understand how to derive distributions if we need new ones. The concept of combinatorials is central to this task and we will start by considering some combinatorial properties.
MINT
发表于 2025-3-26 10:09:05
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根除
发表于 2025-3-26 14:58:40
Two Dimensional and Multi-Dimensional Distributions,haracterized by energy and angle, or temperature and pressure, etc. Sometimes the two variables are completely independent, but often they are strongly correlated. In this chapter, we will examine general two and . dimensional probability distributions and also the generalization of the normal distribution to two and more dimensions.
collagen
发表于 2025-3-26 18:52:28
The Central Limit Theorem,em on this point, the central limit theorem. The normal distribution is the most important probability distribution precisely because of this theorem. We also will find that occasionally in regions of physical interest the assumptions fail and the normal distribution is not approached.